DBMS > AnzoGraph DB vs. ClickHouse vs. CockroachDB vs. ToroDB

System Properties Comparison AnzoGraph DB vs. ClickHouse vs. CockroachDB vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store

Secondary database models

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Website

cambridgesemantics.com/anzograph

clickhouse.com

www.cockroachlabs.com

github.com/torodb/server

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

clickhouse.com/docs

www.cockroachlabs.com/docs

Developer

Cambridge Semantics

Clickhouse Inc.

Cockroach Labs

8Kdata

Initial release

2018

2016

2015

2016

Current release

2.3, January 2021

v24.4.1.2088-stable, May 2024

24.1.0, May 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

Open Source

Apache 2.0, commercial license available

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux

FreeBSD
Linux
macOS

Linux
macOS
Windows

All OS with a Java 7 VM

Data scheme

Schema-free and OWL/RDFS-schema support

yes

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

Close to ANSI SQL (SQL/JSON + extensions)

yes, wire compatible with PostgreSQL

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

JDBC

Supported programming languages

C++
Java
Python

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

key based and custom

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Multi-source replication using RAFT

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Role-based access control

Access rights for users and roles

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